-PDF Download- Data Centric Living EBOOK

Data-centric Living

Author: V. Sridhar

Publisher: Taylor & Francis

Published: 2021-11-29

Total Pages: 305

ISBN-13: 1000483126

This book explores how data about our everyday online behaviour are collected and how they are processed in various ways by algorithms powered by Artificial Intelligence (AI) and Machine Learning (ML). The book investigates the socioeconomic effects of these technologies, and the evolving regulatory landscape that is aiming to nurture the positive effects of these technology evolutions while at the same time curbing possible negative practices. The volume scrutinizes growing concerns on how algorithmic decisions can sometimes be biased and discriminative; how autonomous systems can possibly disrupt and impact the labour markets, resulting in job losses in several traditional sectors while creating unprecedented opportunities in others; the rapid evolution of social media that can be addictive at times resulting in associated mental health issues; and the way digital Identities are evolving around the world and their impact on provisioning of government services. The book also provides an in-depth understanding of regulations around the world to protect privacy of data subjects in the online world; a glimpse of how data is used as a digital public good in combating Covid pandemic; and how ethical standards in autonomous systems are evolving in the digital world. A timely intervention in this fast-evolving field, this book will be useful for scholars and researchers of digital humanities, business and management, internet studies, data sciences, political studies, urban sociology, law, media and cultural studies, sociology, cultural anthropology, and science and technology studies. It will also be of immense interest to the general readers seeking insights on daily digital lives.

Data and Information Quality

Author: Carlo Batini

Publisher: Springer

Published: 2016-03-23

Total Pages: 500

ISBN-13: 3319241060

DOWNLOAD EBOOK →

This book provides a systematic and comparative description of the vast number of research issues related to the quality of data and information. It does so by delivering a sound, integrated and comprehensive overview of the state of the art and future development of data and information quality in databases and information systems. To this end, it presents an extensive description of the techniques that constitute the core of data and information quality research, including record linkage (also called object identification), data integration, error localization and correction, and examines the related techniques in a comprehensive and original methodological framework. Quality dimension definitions and adopted models are also analyzed in detail, and differences between the proposed solutions are highlighted and discussed. Furthermore, while systematically describing data and information quality as an autonomous research area, paradigms and influences deriving from other areas, such as probability theory, statistical data analysis, data mining, knowledge representation, and machine learning are also included. Last not least, the book also highlights very practical solutions, such as methodologies, benchmarks for the most effective techniques, case studies, and examples. The book has been written primarily for researchers in the fields of databases and information management or in natural sciences who are interested in investigating properties of data and information that have an impact on the quality of experiments, processes and on real life. The material presented is also sufficiently self-contained for masters or PhD-level courses, and it covers all the fundamentals and topics without the need for other textbooks. Data and information system administrators and practitioners, who deal with systems exposed to data-quality issues and as a result need a systematization of the field and practical methods in the area, will also benefit from the combination of concrete practical approaches with sound theoretical formalisms.

Life and the Law in the Era of Data-Driven Agency

Author: Mireille Hildebrandt

Publisher: Edward Elgar Publishing

Published: 2020-01-31

Total Pages: 296

ISBN-13: 1788972007

DOWNLOAD EBOOK →

This ground-breaking and timely book explores how big data, artificial intelligence and algorithms are creating new types of agency, and the impact that this is having on our lives and the rule of law. Addressing the issues in a thoughtful, cross-disciplinary manner, leading scholars in law, philosophy, computer science and politics examine the ways in which data-driven agency is transforming democratic practices and the meaning of individual choice.

All Data Are Local

Author: Yanni Alexander Loukissas

Publisher: MIT Press

Published: 2019-04-30

Total Pages: 267

ISBN-13: 0262039664

DOWNLOAD EBOOK →

How to analyze data settings rather than data sets, acknowledging the meaning-making power of the local. In our data-driven society, it is too easy to assume the transparency of data. Instead, Yanni Loukissas argues in All Data Are Local, we should approach data sets with an awareness that data are created by humans and their dutiful machines, at a time, in a place, with the instruments at hand, for audiences that are conditioned to receive them. The term data set implies something discrete, complete, and portable, but it is none of those things. Examining a series of data sources important for understanding the state of public life in the United States—Harvard's Arnold Arboretum, the Digital Public Library of America, UCLA's Television News Archive, and the real estate marketplace Zillow—Loukissas shows us how to analyze data settings rather than data sets. Loukissas sets out six principles: all data are local; data have complex attachments to place; data are collected from heterogeneous sources; data and algorithms are inextricably entangled; interfaces recontextualize data; and data are indexes to local knowledge. He then provides a set of practical guidelines to follow. To make his argument, Loukissas employs a combination of qualitative research on data cultures and exploratory data visualizations. Rebutting the “myth of digital universalism,” Loukissas reminds us of the meaning-making power of the local.

Data Stream Management

Author: Minos Garofalakis

Publisher: Springer

Published: 2016-07-11

Total Pages: 537

ISBN-13: 354028608X

DOWNLOAD EBOOK →

This volume focuses on the theory and practice of data stream management, and the novel challenges this emerging domain poses for data-management algorithms, systems, and applications. The collection of chapters, contributed by authorities in the field, offers a comprehensive introduction to both the algorithmic/theoretical foundations of data streams, as well as the streaming systems and applications built in different domains. A short introductory chapter provides a brief summary of some basic data streaming concepts and models, and discusses the key elements of a generic stream query processing architecture. Subsequently, Part I focuses on basic streaming algorithms for some key analytics functions (e.g., quantiles, norms, join aggregates, heavy hitters) over streaming data. Part II then examines important techniques for basic stream mining tasks (e.g., clustering, classification, frequent itemsets). Part III discusses a number of advanced topics on stream processing algorithms, and Part IV focuses on system and language aspects of data stream processing with surveys of influential system prototypes and language designs. Part V then presents some representative applications of streaming techniques in different domains (e.g., network management, financial analytics). Finally, the volume concludes with an overview of current data streaming products and new application domains (e.g. cloud computing, big data analytics, and complex event processing), and a discussion of future directions in this exciting field. The book provides a comprehensive overview of core concepts and technological foundations, as well as various systems and applications, and is of particular interest to students, lecturers and researchers in the area of data stream management.

Driven by Data

Author: Paul Bambrick-Santoyo

Publisher: John Wiley & Sons

Published: 2010-04-12

Total Pages: 298

ISBN-13: 0470548746

DOWNLOAD EBOOK →

Offers a practical guide for improving schools dramatically that will enable all students from all backgrounds to achieve at high levels. Includes assessment forms, an index, and a DVD.

Data Driven: Harnessing Data and AI to Reinvent Customer Engagement

Author: Tom Chavez

Publisher: McGraw Hill Professional

Published: 2018-10-05

Total Pages: 272

ISBN-13: 1260441547

DOWNLOAD EBOOK →

Axiom Business Book Award Silver Medalist in Business Technology The indispensable guide to data-powered marketing from the team behind the data management platform that helps fuel Salesforce―the #1 customer relationship management (CRM) company in the world A tectonic shift in the practice of marketing is underway. Digital technology, social media, and e-commerce have radically changed the way consumers access information, order products, and shop for services. Using the latest technologies―cloud, mobile, social, internet of things (IoT), and artificial intelligence (AI)―we have more data about consumers and their needs, wants, and affinities than ever before. Data Driven will show you how to: ●Target and delight your customers with unprecedented accuracy and success●Bring customers closer to your brand and inspire them to engage, purchase, and remain loyal●Capture, organize, and analyze data from every source and activate it across every channel●Create a data-powered marketing strategy that can be customized for any audience●Serve individual consumers with highly personalized interactions●Deliver better customer service for the best customer experience●Improve your products and optimize your operating systems●Use AI and IoT to predict the future direction of markets You’ll discover the three principles for building a successful data strategy and the five sources of data-driven power. You’ll see how top companies put these data-driven strategies into action: how Pandora used second- and third-hand data to learn more about its listeners; how Georgia-Pacific moved from scarcity to abundance in the data sphere; and how Dunkin’ Brands leveraged CRM data as a force multiplier for customer engagement. And if you’re wondering what the future holds, you’ll receive seven forecasts to better prepare you for what may come next. Sure to be a classic, Data Driven is a practical road map to the modern marketing landscape and a toolkit for success in the face of changes already underway and still to come.

Data-driven Multivalence in the Built Environment

Author: Nimish Biloria

Publisher: Springer

Published: 2019-07-01

Total Pages: 338

ISBN-13: 3030121801

DOWNLOAD EBOOK →

This book sets the stage for understanding how the exponential escalation of digital ubiquity in the contemporary environment is being absorbed, modulated, processed and actively used for enhancing the performance of our built environment. S.M.A.R.T., in this context, is thus used as an acronym for Systems & Materials in Architectural Research and Technology, with a specific focus on interrogating the intricate relationship between information systems and associative material, cultural and socioeconomic formations within the built environment. This interrogation is deeply rooted in exploring inter-disciplinary research and design strategies involving nonlinear processes for developing meta-design systems, evidence based design solutions and methodological frameworks, some of which, are presented in this issue. Urban health and wellbeing, urban mobility and infrastructure, smart manufacturing, Interaction Design, Urban Design & Planning as well as Data Science, as prominent symbiotic domains constituting the Built Environment are represented in this first book in the S.M.A.R.T. series. The spectrum of chapters included in this volume helps in understanding the multivalence of data from a socio-technical perspective and provides insight into the methodological nuances involved in capturing, analysing and improving urban life via data driven technologies.

DATA CENTRIC.NET,

Author: Jacob Hammer Pederson

Publisher: Apress

Published: 2001-12-23

Total Pages: 822

ISBN-13: 9781861005922

DOWNLOAD EBOOK →

The development of the .NET Framework, with the associated release of the C# programming language, is set to stimulate a new wave of application development. This book aims to provide the information needed to develop powerful data-centric applications using C#. To do this it covers the new features of ADO.NET that deliver efficient data access and manipulation, and the XML handling capabilities of the .NET Framework. Accepting that data-centric applications will utilize a variety of sources and inputs, it also looks at additional topics such as using ADO with C#, Messaging Services, and utililizing the Registry and Active Directory. This information is put into context within a number of case studies including one showing how to migrate an application from Visual Basic 6 to C#.

Software Wasteland

Author: Dave McComb

Publisher:

Published: 2018-02-05

Total Pages: 250

ISBN-13: 9781634623162

DOWNLOAD EBOOK →

Know what's causing application development waste so you can turn the tide. This is the book your Systems Integrator and your Application Software vendor don't want you to read. Enterprise IT (Information Technology) is a $3.8 trillion per year industry worldwide. Most of it is waste. We've grown used to projects costing tens of millions or even billions of dollars, and routinely running over budget and schedule many times over. These overages in both time and money are almost all wasted resources. However, the waste is hard to see, after being so marbled through all the products, processes, and guiding principles. That is what this book is about. We must see, understand, and agree about the problem before we can take coordinated action to address it. The trajectory of this book is as follows: In Chapter 1, we explore how bad the current state is. The three industries that address software waste are discussed, including the legacy software industry, neo-legacy software industry, and legacy modernization industry. Examples of application waste are illustrated from both public and private sectors. In Chapter 2, we explore the economics of the software industry. Although the economic tradeoffs are changing at the speed of Moore's Law, our approaches are not keeping pace. Learn how information systems really behave in terms of actual application development. In Chapter 3 we use "root cause analysis" to reveal the real contributors to this situation, which are dependency, redundancy, complexity, and application centricity. Chapter 4 recounts the many failed attempts we've made in the past to deal with information system complexity, including relational databases, ERP systems, enterprise data modeling, service oriented architectures, and APIs, Agile, data warehouse and business intelligence, outsourcing and offshoring, cloud, Software as a Service (SaaS), data lakes, machine learning, and artificial intelligence. Chapter 5 dismantles seven fallacies that contribute to our remaining stuck. For example, the first fallacy is "We need detailed requirements or we won't get what we want." The quagmire is not affecting all sectors of the economy equally. Chapter 6 looks at how this is playing out in the government and private sectors, large and small companies, and various parts of the IT industry itself. Chapter 7 outlines some action you can take now to begin to extricate yourself, including a detailed assessment and defining metrics for measuring and preventing software development waste.